EARTH SCIENCE | CLIMATE INDICATORS | ATMOSPHERIC/OCEAN INDICATORS | EXTREME WEATHER
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'Weather@home ANZ' is a global citizen science distributed computing project being run as part of the Oxford-based 'weather@home' project, which is part of 'climateprediction.net'. In this experiment, a detailed limited area (regional) climate model is embedded within the less detailed 'driving' global model. This higher-resolution regional model is able to tell us in unprecedented detail about potential changes to patterns of weather as climate changes. In the initial 'weather@home' experiment launched in 2010, the project team released this regional modelling capability for three regions: Europe, Southern Africa and the Western USA. This capability has been extended to other regions around the world and the first such new region to be developed was the Australasian region encompassing Australia, New Zealand and surrounding areas, which was launched to the public in 2014. This particular part of the project - 'weatherathome ANZ' - has received support from the University of Oxford (U.K.), the U.K. Met. Office, the Universities of Melbourne and Tasmania (Australia), the Tasmanian Partnership for Advanced Computing and the New Zealand National Institute for Water and Atmospheric Research (NIWA). 'weather@home' has also been supported by Microsoft Research.
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We have used a quantitative definition of marine heatwaves to detect all events which have occurred in 12 regions across the continental shelf off eastern Tasmania over 1993-2015. For each event in each region this atlas includes information on (i) event properties including intensity, duration and depth, (ii) maps of regional ocean circulation and ocean temperature during the event, and (iii) maps of regional atmospheric conditions during the event (air temperature and surface wind). Also provided are summary statistics including the typical conditions which give rise to marine heatwaves in each region and annual time series demonstrating interannual variability and long term trends in marine heatwave properties. Provided is a comprehensive document presenting the atlas and a set of CSV files containing the underlying data.
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Globally, terrestrially-breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to assess likely climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. Our results identified shy albatross (Thalassarche cauta), southern rockhopper penguins (Eudyptes chrysocome), Australian fur seals (Arctocephalus pusillus doriferus), and Australian sea lions (Neophoca cinerea) with high climate urgency. Species breeding in lower latitudes as well as certain eared seal, albatross, and penguin species were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazard criteria, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.